Most people who have teleoperated a robotic system easily recognize the challenges imposed by the reduced situational awareness, and the effects of delays and poor communications. Control of SUGVs in cluttered environments requires fine control of the platform to avoid obstacles, and align the platforms with doorways or stairways. On larger UGVs, speed is normally paramount for mission success, and communication delays can cause control instabilities that often result in overturned or damaged vehicles.
Recent developments in UGVs have led to significant increases in military spending. It is estimated that global spending on UGVs reached $418 million in 2010 [12]. As the capabilities of these UGVs are expanded past Explosive Ordnance Disposal (EOD) and into perimeter surveillance, logistics support and armed combat, the market is expected to grow to upwards of $2.9 billion by 2016. This growth will primarily be driven by military, homeland security and law enforcement sectors. In particular, the U.S, military will be a significant engine of growth due to a Congressionally Directed Goal of ⅓ of ground combat vehicles should be unmanned by 2015.
With bombs, mines and improvised explosive devices (IEDs) littering the battlefield, soldier's lives are put at extremely high risk during bomb diffusion missions. Militaries have sought many ways to reduce the exposure of personnel to such hazardous conditions. Robots offer the perfect solution. Extensive research is being done on teleoperation and ways to remotely control the aforementioned robots. For these robots to be used effectively, information from sensors, microphones and cameras must be relayed in real time or create a “virtual real time” experience. Extreme precision and complete situational awareness is needed when detecting and disarming explosives.
The ongoing battle in the Middle East has caused a spike in interest in these robotic soldiers. According to Lieutenant General Michael Oates, in 2011 “IEDs are still responsible for the greatest number of our casualties in Iraq and Afghanistan”. Such danger has been reduced drastically, 37 percent, thanks in part to the militaries increased use of drones to detect IEDs. Still, however, insurgents show no sign of slowing, as the number of IEDs planted are between 1,300 and 1,500 per month, increasing the need for more EOD robots to be deployed.
Intelligence gathering has been a staple of warfare since the beginning of organized combat, and without which any army is bound to fail. Often, these missions leave soldiers exposed and vulnerable to attacks when surveying, especially behind enemy lines. Modern warfare has allowed the Inventors to utilize unmanned vehicles to carry out such missions. Replacing soldiers with unmanned vehicles not only allows for more in depth surveillance, but also saves the lives of those soldiers sent on reconnaissance missions. Further, robots can operate for hours without fatigue and loss of perception unlike humans, increasing their effectiveness at evaluating enemy positions and territory. In 2001, the military had commissioned only 120 teleoperated robots for use in the Middle Eastern. As of 2008, however, ground robots had increased to more than 6,000 in theater.
This massive spike in interest and demand for unmanned vehicles has increased the need for an improved and reliable visual processing algorithm to reduce, or even completely remove, data transmission lag between robot and operator. Control of SUGVs in cluttered environments requires fine control of the platform to avoid obstacles, and align the platforms with doorways or stairways. On larger UGVs, speed is normally paramount for mission success, and communication delays can cause control instabilities that often result in overturned or damaged vehicles. In order to improve the teleoperator's ability to control the robot, algorithms that create future synthetic images, and predict platform poses are used to create an image on the Operator Control Unit screen that smoothes out the stops/starts/jumps and irregular video feed. Currently, operators must be in the line of sight of the robot, otherwise serious data transmission lag can occur, rendering them ineffective. Additionally, this lag can cause cognitive fatigue in the operator, causing headaches and stress. These time delays can cause operations to go awry. The Darkstar UAV had a seven (7) second delay between remote command and implementation. The operators were not able to send commands to the Darkstar in time, resulting in an unpredictable crash during take-off. Such events have sparked significant demand for predictive displays to eliminate lag, cognitive fatigue, and increase remote operation distances.